The remaining (fourth and fifth) limitations require future work to be addressed.
Fourth, SLS assumes all training data uses the same training labels. Semi-supervised approaches cannot be correctly represented by SLS.
Fifth, multi-modal data is not captured. For example, in Table REF  the method TBN [1]} utilises audio information in addition to video, giving it an advantage. Similarly, when performing tasks like retrieval or captioning, two modalities (vision + langauage) will consider different SLS for each modality. We leave this consideration of multiple modalities and their relationship to SLS for future work and focus only on the visual modality.
